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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 1,243 records · Page 69
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Perturbative study of the one-dimensional quantum clock model

In this report we calculate the ground-state energy density ε(g) for the one-dimensional N-state quantum clock model up to order 18, where g is the coupling and N = 3,4,5,...,10, 20. Using methods based on the Padé approximation, we extract the singular structure of ε"(g) or ε(g). They correspond to the specific heat and free energy of the classical two-dimensional (2D) clock model. We find that, for N = 3, 4, there is a single critical point at g c = 1. The heat capacity exponent of the corresponding 2D classical model is α = 0.34 ± 0.01 for N = 3, and α = - 0.01 ± 0.01 for N = 4. For N > 4, there are two exponential singularities related by g c1 = 1/g c2 , and ε(g) behaves as Ae - $\frac{c}{|g_c -g|^a}$ + analytic terms near g c . The exponent σ gradually grows from 0.2 to 0.5 as N increases from 5 to 9, and it stabilizes at 0.5 when N > 9. The phase transitions exhibited in these models should be generalizations of the Kosterlitz-Thouless transition, which has σ = 0.5 .

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2015

Iterative spectral method for solving electrostatic or magnetostatic problems in complex and evolving heterostructures

Electrostatic or magnetostatic problems involving complex heterogeneity are nontrivial for modeling and simulation. Most existing numerical methods focus on sharp interface models and the computational cost increases with increasing complexity of the geometry. Here we develop an iterative spectral method, the bound charge successive approximation algorithm, to solve electrostatic or magnetostatic heterogeneity problems in the context of diffuse-interface modeling. As tests and verifications, this algorithm is applied to calculation of the depolarization factor of an ellipsoid, and simulation of random dielectric mixtures and the dielectophoretic motion of multiple particles. The algorithm shows excellent efficiency and the computational cost mainly depends on the permittivity or permeability contrast in the whole system, regardless of the complexity of the geometry. Specifically, for evolving heterostructures the solution of bound charge in one time step can be used as input for the next, which could further significantly shorten the iteration (approximation) process, making it practical to simulate the long-range electrostatic or magnetostatic interaction in complex and evolving heterostructures.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Global Explainability of A Deep Abstaining Classifier for Cancer Pathology Reports

We present a global explainability method to characterize sources of errors in a real-world multitask deep abstaining classifier (DAC), in the context of cancer histology prediction. Our multitask classifier, currently deployed for automated annotation of cancer pathology reports from NCI-SEER registries, was trained and evaluated on 1.04 million hand-annotated samples and makes simultaneous predictions of cancer site, subsite, histology, laterality, and behavior for each report. The DAC framework enables the model to abstain on ambiguous reports and confusing classes to achieve the target accuracy on the retained (non-abstained) samples, but at the cost of decreased coverage. Requiring 97% accuracy on the histology task caused our model to retain only 22% of all samples, mostly the less ambiguous and common classes. Local explainability with the GradInp technique provided a computationally efficient way of obtaining contextual reasoning for hundreds of thousands of individual predictions. Our method, involving dimensionality reduction of approximately 13000 aggregated local explanations (ALE), offers a tractable path to true global explainability. It enabled identification of sources of errors in histology classification, globally, as hierarchical complexity among classes, label noise, insufficient information, and conflicting evidence. This suggests several strategies for iterative improvement of our DAC, including well-designed exclusion criteria, focused annotation, and reduced penalties for errors involving hierarchically related classes.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2018

Simulation-Based Parameter Optimization Framework for Large-Scale Hybrid Smart Grid Communications Systems Design

The design of reliable, dynamic, fault-tolerant hybrid smart grid communication networks is a challenge to achieve for autonomous power grids. Hybrid networks use different communications technologies for different area networks. A simulation-based parameter optimization framework is proposed to tune parameters of hybrid communication technologies to achieve the optimal network performance. It consists of three main components: a parallel executor used to speedup a list of simulations; a sampler running simulations using the parallel executor at each generation; and a hybrid stochastic optimization algorithm for tuning configurable parameters of hybrid designs and applications. The proposed hybrid metaheuristic optimization algorithm combines an evolutionary algorithm with a gradient method to quickly achieve an approximately global optimum solution. Three optimization test functions are employed to train the adjustable parameters of the hybrid algorithm. Results show the proposed parameter optimization framework can help the designer choose the right hybrid architecture with an optimal parameter set for a large-scale broadband PLC-WiMAX hybrid smart grid communication network.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2014

Land cover classification in multispectral imagery using clustering of sparse approximations over learned feature dictionaries

We present results from an ongoing effort to extend neuromimetic machine vision algorithms to multispectral data using adaptive signal processing combined with compressive sensing and machine learning techniques. Our goal is to develop a robust classification methodology that will allow for automated discretization of the landscape into distinct units based on attributes such as vegetation, surface hydrological properties, and topographic/geomorphic characteristics. We use a Hebbian learning rule to build spectral-textural dictionaries that are tailored for classification. We learn our dictionaries from millions of overlapping multispectral image patches and then use a pursuit search to generate classification features. Land cover labels are automatically generated using unsupervised clustering of sparse approximations (CoSA). We demonstrate our method on multispectral WorldView-2 data from a coastal plain ecosystem in Barrow, Alaska. We explore learning from both raw multispectral imagery and normalized band difference indices. We explore a quantitative metric to evaluate the spectral properties of the clusters in order to potentially aid in assigning land cover categories to the cluster labels. In this study, our results suggest CoSA is a promising approach to unsupervised land cover classification in high-resolution satellite imagery.

42 ENGINEERING↗
DOE OSTI2014

TH-A-18C-02: An Electrostatic Model for Assessment of Joint Space Morphology in Cone-Beam CT

Purpose: High-resolution cone-beam CT (CBCT) of the extremities presents a potentially valuable basis for image-based biomarkers of arthritis, trauma, and risk of injury. We present a new method for 3D joint space analysis that exploits the high isotropic spatial resolution of CBCT and is sensitive to small changes in disease-related morphology. Methods: The approach uses an “electrostatic” model in which joint surfaces (e.g., distal femur and proximal tibia) are labeled as charge densities between which the electric field is solved by approximation to the Laplace equation. The method yields a unique solution determined by the field lines across the “capacitor” and is hypothesized to be more sensitive than conventional (Sharp) scores and immune to degeneracies that limit simple distance-along-axis or closest-point analysis. The algorithm was validated in CBCT phantom images and applied in two clinical scenarios: osteoarthritis (OA, change in loadbearing tibiofemoral joint space); and assessment of injury risk (correlation of 3D joint space to tibial slope). Results: Joint space maps computed from the electrostatic model were accurate to within the voxel size (0.26 mm). The method highlighted subtle regions of morphological change that would likely be missed by conventional scalar metrics. Regions of subtle cartilage erosion were well quantified, and the method confidently discriminated OA and non-OA cohorts. 3D joint space maps correlated well with tibial slope and provide a new basis for principal component analysis of loadbearing injury risk. Runtime was less than 5 min (235×235×121 voxel subvolume in Matlab). Conclusion: A new method for joint space assessment was reported as a possible image-based biomarker of subtle articular change. The algorithm yields accurate quantitation of the joint in a manner that is robust against operator and patient setup variation. The method shows promising initial results in ongoing trials of CBCT in osteoarthritis, rheumatoid arthritis, and injury risk assessment. Research supported by R01 and R21 grants from the National Institutes of Health, academic-industry partnership with Carestream Health, and a grant from the US Army Natick Soldier Research, Development and Engineering Center.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2016

TU-AB-BRC-12: Optimized Parallel MonteCarlo Dose Calculations for Secondary MU Checks

Purpose: Secondary MU checks are an important tool used during a physics review of a treatment plan. Commercial software packages offer varying degrees of theoretical dose calculation accuracy, depending on the modality involved. Dose calculations of VMAT plans are especially prone to error due to the large approximations involved. Monte Carlo (MC) methods are not commonly used due to their long run times. We investigated two methods to increase the computational efficiency of MC dose simulations with the BEAMnrc code. Distributed computing resources, along with optimized code compilation, will allow for accurate and efficient VMAT dose calculations. Methods: The BEAMnrc package was installed on a high performance computing cluster accessible to our clinic. MATLAB and PYTHON scripts were developed to convert a clinical VMAT DICOM plan into BEAMnrc input files. The BEAMnrc installation was optimized by running the VMAT simulations through profiling tools which indicated the behavior of the constituent routines in the code, e.g. the bremsstrahlung splitting routine, and the specified random number generator. This information aided in determining the most efficient compiling parallel configuration for the specific CPU’s available on our cluster, resulting in the fastest VMAT simulation times. Our method was evaluated with calculations involving 10{sup 8} – 10{sup 9} particle histories which are sufficient to verify patient dose using VMAT. Results: Parallelization allowed the calculation of patient dose on the order of 10 – 15 hours with 100 parallel jobs. Due to the compiler optimization process, further speed increases of 23% were achieved when compared with the open-source compiler BEAMnrc packages. Conclusion: Analysis of the BEAMnrc code allowed us to optimize the compiler configuration for VMAT dose calculations. In future work, the optimized MC code, in conjunction with the parallel processing capabilities of BEAMnrc, will be applied to provide accurate and efficient secondary MU checks.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2018

Witnessing eigenstates for quantum simulation of Hamiltonian spectra

The efficient calculation of Hamiltonian spectra, a problem often intractable on classical machines, can find application in many fields, from physics to chemistry. We introduce the concept of an “eigenstate witness” and, through it, provide a new quantum approach that combines variational methods and phase estimation to approximate eigenvalues for both ground and excited states. This protocol is experimentally verified on a programmable silicon quantum photonic chip, a mass-manufacturable platform, which embeds entangled state generation, arbitrary controlled unitary operations, and projective measurements. Both ground and excited states are experimentally found with fidelities >99%, and their eigenvalues are estimated with 32 bits of precision. We also investigate and discuss the scalability of the approach and study its performance through numerical simulations of more complex Hamiltonians. This result shows promising progress toward quantum chemistry on quantum computers.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2018

The Energy Spectrum and Optical Properties of Fullerene C{sub 70} within the Hubbard Model

The energy spectrum of fullerene C{sub 70} is calculated within the Hubbard model in the mean-field approximation. Using group-theory methods, irreducible representations are determined that correspond to the energy states, as well as allowed transitions in the energy spectrum of fullerene C{sub 70}. On the basis of this spectrum, an interpretation of experimentally observed optical absorption bands of fullerene C{sub 70} is proposed.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2015

Theoretical study of oxygen sorption and diffusion in the volume and on the surface of a γ-TiAl alloy

The oxygen sorption on the low-index (001), (100), and (110) surfaces of a γ-TiAl alloy is studied by the pseudopotential method with the generalized gradient approximation for the exchange-correlation functional. The most preferred sites for oxygen sorption in the bulk and on the surface of the alloy are determined. The titanium-rich octahedral site is shown to be preferred for oxygen sorption in the bulk material. The effect of the oxygen concentration on the atomic and electronic structures of the stoichiometric TiAl(100) surface is studied. It is shown that, at the first stage of oxidation, oxygen prefers to form bonds with titanium. The energy barriers for oxygen diffusion on the stoichiometric (100) surface and in the bulk of the material are calculated. The energy barriers are shown to depend substantially on the local environments of oxygen and to increase during diffusion from titanium-rich sites. The most possible mechanism of oxygen diffusion from the (100) surface to the bulk of the material is oxygen migration through tetrahedral sites.

36 MATERIALS SCIENCE↗
DOE OSTI2017

Analysis of macroparticle charge screening in a nonequilibrium plasma based on the kinetic collisional point sink model

The screening of macroparticles in a nonequilibrium plasma is considered on the basis of the Vlasov kinetic equations supplemented with the collisional term in the Bhatnagar–Gross–Krook approximation and the point sink method. In this method, the absorption of electrons and ions by a macroparticle is described by introducing effective point sinks into the kinetic equations for plasma electrons and ions. Explicit expressions are derived for the potential distribution around a macroparticle and effective charges that determine the behavior of the potential at large distances taking into account collisions of electrons and ions with neutral buffer gas atoms. We consider the cases of a constant collision frequency and constant mean free paths of electrons and ions in the buffer gas. Numerical calculations are performed for dusty isothermal and nonisothermal plasmas in helium, neon, argon, krypton, and xenon at pressures of 10{sup –1} to 10{sup 4} Pa, which are typical of experiments with dusty plasmas.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2016

Self-consistent approach to beta decay and delayed neutron emission

A brief overview of the recent self-consistent studies of nuclear beta decay is given including the relativistic quasi-particle random-phase approximation or QRPA and Finite Amplitude Method. The results of our self-consistent continuum QRPA model based on the density functional description of the ground states are presented. They are in a good agreement with the recent experimental beta-decay half-lives and delayed neutron emission branchings for the nuclei approaching (and beyond) the neutron closed shells N = 50 near {sup 78}Ni and N = 82 near {sup 132}Sn. A comparison with the recent calculations from relativistic QRPA model, Finite Amplitude Method and semi-microscopic finite-range droplet model is performed. An importance of the quasi-particle phonon coupling is stressed for the description of the beta decay and delayed multi-neutron emission rates. A strategy of extending our approach to the deformed nuclei and the open problems are discussed.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2018

Kinetics of CO Molecules Taking into Account Resonant VE Exchanges in a Nonequilibrium Nozzle Flow

The kinetics of CO molecules with excited electronic levels for a nonequilibrium flow in nozzles is studied. Three electronic energy levels are taken into account; the VV exchanges of the vibrational energy within each electronic energy level, VT transitions from the vibrational energy to the translational energy, and VE exchanges between the vibrational energy and the electronic terms occur in the system. The system of equations of vibrational level kinetics and gasdynamics, which is written in the zeroth approximation of the Chapman–Enskog method, is solved numerically. Special attention is paid to estimating the effect of the VE exchanges of the vibrational energy on the formation of nonequilibrium populations of the vibrational levels. It is shown that resonant VE transitions considerably affect the relaxation process and noticeably change the population of the upper vibrational levels even in the absence of recombination and dissociation processes; VE exchanges also affect the time dependence of the vibrational temperature.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2019

The Bloch equation for spin dynamics in electron storage rings: Computational and theoretical aspects

In this paper, we describe our work on spin polarization in high-energy electron storage rings which we base on the Full Bloch equation (FBE) for the polarization density and which aims towards the [Formula: see text] option of the proposed Future Circular Collider (FCC-ee) and the proposed Circular Electron Positron Collider (CEPC). The FBE takes into account non spin-flip and spin-flip effects due to synchrotron radiation including the spin-diffusion effects and the Sokolov–Ternov effect with its Baier–Katkov generalization as well as the kinetic-polarization effect. This mathematical model is an alternative to the standard mathematical model based on the Derbenev–Kondratenko formulas. For our numerical and analytical studies of the FBE, we develop an approximation to the latter to obtain an effective FBE. This is accomplished by finding a third mathematical model based on a system of stochastic differential equations (SDEs) underlying the FBE and by approximating that system via the method of averaging from perturbative ODE theory. We also give an overview of our algorithm for numerically integrating the effective FBE. This discretizes the phase space using spectral methods and discretizes time via the additive Runge–Kutta (ARK) method which is a high-order semi-implicit method. We also discuss the relevance of the third mathematical model for spin tracking.

Physics↗
DOE OSTI2025

Self-supervised physics-informed generative networks for phase retrieval from a single X-ray hologram

X-ray phase contrast imaging significantly improves the visualization of structures with weak or uniform absorption, broadening its applications across a wide range of scientific disciplines. Propagation-based phase contrast is particularly suitable for time- or dose-critical in vivo/in situ/operando (tomography) experiments because it requires only a single intensity measurement. However, the phase information of the wave field is lost during the measurement and must be recovered. Conventional algebraic and iterative methods often rely on specific approximations or boundary conditions that may not be met by many samples or experimental setups. In addition, they require manual tuning of reconstruction parameters by experts, making them less adaptable for complex or variable conditions. Here we present a self-learning approach for solving the inverse problem of phase retrieval in the near-field regime of Fresnel theory using a single intensity measurement (hologram). A physics-informed generative adversarial network is employed to reconstruct both the phase and absorbance of the unpropagated wave field in the sample plane from a single hologram. Unlike most state-of-the-art deep learning approaches for phase retrieval, our approach does not require paired, unpaired, or simulated training data. This significantly broadens the applicability of our approach, as acquiring or generating suitable training data remains a major challenge due to the wide variability in sample types and experimental configurations. The algorithm demonstrates robust and consistent performance across diverse imaging conditions and sample types, delivering quantitative, high-quality reconstructions for both simulated data and experimental datasets acquired at beamline P05 at PETRA III (DESY, Hamburg), operated by Helmholtz-Zentrum Hereon. Furthermore, it enables the simultaneous retrieval of both phase and absorption information.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Geothermal Fault Zone and Fluid Imaging through Joint Airborne ZTEM and Ground MT Data Inversion Analysis

This project has aimed to achieve detailed electrical resistivity resolution at geothermal reservoir scales by combining airborne natural electromagnetic (EM) field surveying (ZTEM) with ground magnetotelluric (MT) measurements to approximate an airborne MT geophysical method. MT alone is relatively expensive and may have permitting challenges in sensitive areas. Airborne ZTEM field data contains only the magnetic field, requires a background assumption, and has been limited to relatively high frequencies, thus suffering uniqueness problems. Based on proto-type 2D simulations, ZTEM ambiguities may be reduced through formal incorporation with possibly sparse ground MT soundings, which we pursued in full 3D for this project. The methodology was tested at the high-temperature Roosevelt Hot Springs geothermal system, Utah, which was considered advantageous given the near total exposure of crystalline reservoir rocks across the project area. ZTEM and ground MT survey data were acquired in 2017, subcontracted to outside parties with which we have worked in the past. These included 80 remote-referenced tensor MT soundings over the Mineral Mountains and adjacent Roosevelt Hot Spring producing geothermal system. These MT stations abut later coverage of a similar number of MT stations taken for the Utah FORGE project providing excellent total data aperture to re-solve structure beneath both project areas better than either set alone. The airborne ZTEM survey covered 704 line kilometers in E-W flight lines with a 250 m line spacing. Although this survey was timed during a maintenance-related shutdown of power production at the Roosevelt Hot Springs, other noise sources difficult to identify but including two high-voltage state-scale transmission lines compromised the ZTEM survey badly leading to unusable responses. Thus, with DOE management concurrence, the project proceeded to emphasize inversion and interpretation of the joint SubTER-FORGE MT data sets with regard to the Roosevelt Hot Springs reservoir recharge and to deep heat sources for both it and the Utah FORGE EGS project area. We also investigated the joint ZTEM-MT sampling concept with data sets from the Eleven Mile Canyon prospect area donated by the U.S. Navy (A. Sabin, PoC). Inversion of the SubTER-FORGE MT data using the HexMT 3D finite element algorithm reveals a large, low-resistivity anomaly extending sub-vertically through the depth range of the crust beneath the western Mineral Mountains. The steep conductive zone connects in the lower crust to a more tabular conductor characteristic of much of the Great Basin that generally is ascribed to current mafic magmatic underplating, hybridization and fluid release. The location of the resolved anomaly relative to the recent (0.5-0.8 Ma) eruptive centers of the Mineral Mountains implicates it as remnants of the magma body which fed these centers. This structure appears to be currently feeding heat and fluids upward into the Roosevelt Hot Springs hydrothermal system, as well as heat laterally to the FORGE project area. Separate and joint inversion models were carried out for the donated Eleven Mile Canyon MT-ZTEM data set to demonstrate concept. ZTEM only inversion showed two main alteration zones in the western portion of the project area known from geological mapping. Joint inversion including an E-W profile of MT soundings sharpened these features considerably. It also resolved in much greater detail the graben related normal faulting structure of the central project area which lies at depths exceeding the sensitivity of ZTEM alone. The sparse number of MT da-ta relative to the ZTEM required upweighting the former by a factor of several, but an exact procedure awaits future research. Our final impression is that sparse MT data can improve resolution of the subsurface over that of ZTEM alone. However, well sampled MT data are to be preferred and offer the simplicity of interpreting just one data type, and possess the superior resolution capability coming with the electric field everywhere, and from their high bandwidth.

15 GEOTHERMAL ENERGY↗
DOE OSTI2024

Optoelectronic properties of bent two-dimensional materials from first-principles methods combined with machine learning

A material’s interaction with light is highly relevant in the design of nanoelectronic devices such as photodiodes, solar cells, photocatalytic cells, phototransistors, and photodetectors. The interaction of a material with light can be altered by mechanical deformation. Fine tuning of the optical properties can be achieved by mechanical bending that alters the electronic structure. Optical properties strongly depend on band gaps, therefore any alteration in the band structure results in a changed optical response of the material. The impact of bending was explored in this project. The goal of this project was to assess the impact of mechanical bending of two-dimensional transition metal dichalcogenides on their optoelectronic properties, using first-principles methods. These first-principles approximations are largely built upon many-body theory for the optical properties of magnetic and topological nanoribbons. GW-BSE is standard for optical absorption, but it is less practical for collective excitations as it was shown in model systems. Time-dependent density functional theory, however, has better promises for collective excitations in low-dimensional materials.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Implementation of Perturbation Theory and Sensitivity Capabilities in Griffin

Griffin is a Multiphysics Object-Oriented Simulation Environment (MOOSE) based reactor Multiphysics analysis application, jointly developed by Argonne and Idaho National Laboratories under the DOE-NE NEAMS program. This fiscal year, capabilities for reactivity and sensitivity evaluation using perturbation methods were implemented and verified. The First Order Perturbation Method (FOPT) was employed to compute reactivity worth resulting from small perturbations in input parameters, while the Generalized Perturbation Theory (GPT) was used to evaluate sensitivities of a range of response types, including reaction rate ratio, k-eigenvalue, neutron generation time, and effective delayed neutron fraction. These perturbation methods enable users to quantify how response quantities change due to a perturbation in a input parameter without explicitly performing an additional transport simulation for each perturbed state. In particular, the GPT formulation accounts for indirect effects arising from flux changes by solving generalized inhomogeneous equations, for which a Neumann series-based iterative solution method was developed and implemented in Griffin. The implemented reactivity and sensitivity evaluation capabilities were verified using two test problems: an infinite homogeneous system and a two-dimensional hexagonal core. The results showed excellent agreement with reference solutions obtained by a direct method based on finite difference approximation as well as GPT-based results from the PERSENT code, confirming the accuracy of both reactivity and sensitivity evaluations. Additionally, preliminary uncertainty quantification (UQ) results were obtained by combining the sensitivity values computed using GPT and external covariance data, demonstrating that the implemented sensitivity results can be reliably used for uncertainty calculations. To further demonstrate the generality and practical strength of the implementation, the sensitivity evaluation capability was successfully applied to the Empire microreactor with a geometrically complex design that poses significant modeling challenges. The results confirm that Griffin enables sensitivity evaluations even for irregular and highly heterogeneous reactor configurations, thereby establishing a foundation for UQ applications in advanced reactor designs and analyses.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗